Category Archives: Social Media

How do international humanitarian organizations make sense of the “Big Data” generated during major disasters? They turn to Digital Humanitarians who craft and leverage ingenious crowdsourcing solutions with trail-blazing insights from artificial intelligence to make sense of vast volumes of social media, satellite imagery and even UAV/aerial imagery. They also use these “Big Data” solutions to verify user-generated content and counter rumors during disasters. The talk below explains how Digital Humanitarians do this and how their next generation humanitarian technologies work.

Many thanks to TTI/Vanguard for having invited me to speak. Lots more on Digital Humanitarians in my new book of the same title.

Videos of my TEDx talks and the talks I’ve given at the White House, PopTech, Where 2.0, National Geographic, etc., are all available here.

In January 2014, I wrote this blog post announcing my intention to write a book on Digital Humanitarians. Well, it’s done! And launches this week. The book has already been endorsed by scholars at Harvard, MIT, Stanford, Oxford, etc; by practitioners at the United Nations, World Bank, Red Cross, USAID, DfID, etc; and by others including Twitter and National Geographic. These and many more endorsements are available here. Brief summaries of each book chapter are available here; and the short video below provides an excellent overview of the topics covered in the book. Together, these overviews make it clear that this book is directly relevant to many other fields including journalism, human rights, development, activism, business management, computing, ethics, social science, data science, etc. In short, the lessons that digital humanitarians have learned (often the hard way) over the years and the important insights they have gained are directly applicable to fields well beyond the humanitarian space. To this end, Digital Humanitarians is written in a “narrative and conversational style” rather than with dense, technical language.

The story of digital humanitarians is a multifaceted one. Theirs is not just a story about using new technologies to make sense of “Big Data”. For the most part, digital humanitarians are volunteers; volunteers from all walks of life and who occupy every time zone. Many are very tech-savvy and pull all-nighters, but most simply want to make a difference using the few minutes they have with the digital technologies already at their fingertips. Digital humanitarians also include pro-democracy activists who live in countries ruled by tyrants. This story is thus also about hope and humanity; about how technology can extendour humanity during crises. To be sure, if no one cared, if no one felt compelled to help others in need, or to change the status quo, then no one even would bother to use these new, next generation humanitarian technologies in the first place.

I believe this explains why Professor Leysia Palen included the following in her very kind review of my book: “I dare you to read this book and not have both your heart and mind opened.” As I reflected to my editor while in the midst of book writing, an alternative tag line for the title could very well be “How Big Data and Big Hearts are Changing the Face of Humanitarian Response.” It is personally and deeply important to me that the media, would-be volunteers and others also understand that the digital humanitarians story is not a romanticized story about a few “lone heroes” who accomplish the impossible thanks to their super human technical powers. There are thousands upon thousands of largely anonymous digital volunteers from all around the world who make this story possible. And while we may not know all their names, we certainly do know about their tireless collective action efforts—they mobilize online from all corners of our Blue Planet to support humanitarian efforts. My book explains how these digital volunteers do this, and yes, how you can too.

Digital humanitarians also include a small (but growing) number of forward-thinking professionals from large and well-known humanitarian organizations. After the tragic, nightmarish earthquake that struck Haiti in January 2010, these seasoned and open-minded humanitarians quickly realized that making sense of “Big Data” during future disasters would require new thinking, new risk-taking, new partnerships, and next generation humanitarian technologies. This story thus includes the invaluable contributions of those change-agents and explains how these few individuals are enabling innovation within the large bureaucracies they work in. The story would thus be incomplete without these individuals; without their appetite for risk-taking, their strategic understanding of how to change (and at times circumvent) established systems from the inside to make their organizations still relevant in a hyper-connected world. This may explain why Tarun Sarwal of the International Committee of the Red Cross (ICRC) in Geneva included these words (of warning) in his kind review: “For anyone in the Humanitarian sector — ignore this book at your peril.”

Today, this growing, cross-disciplinary community of digital humanitarians are crafting and leveraging ingenious crowdsourcing solutions with trail-blazing insights from advanced computing and artificial intelligence in order to make sense of “Big Data” generated during disasters. In virtually real-time, these new solutions (many still in early prototype stages) enable digital volunteers to make sense of vast volumes of social media, SMS and imagery captured from satellites & UAVs to support relief efforts worldwide.

All of this obviously comes with a great many challenges. I certainly don’t shy away from these in the book (despite my being an eternal optimist : ). As Ethan Zuckerman from MIT very kindly wrote in his review of the book,

“[Patrick] is also a careful scholar who thinks deeply about the limits and potential dangers of data-centric approaches. His book offers both inspiration for those around the world who want to improve our disaster response and a set of fertile challenges to ensure we use data wisely and ethically.”

Digital humanitarians are not perfect, they’re human, they make mistakes, they fail; innovation, after all, takes experimenting, risk-taking and failing. But most importantly, these digital pioneers learn, innovate and over time make fewer mistakes. In sum, this book charts the sudden and spectacular rise of these digital humanitarians and their next generation technologies by sharing their remarkable, real-life stories and the many lessons they have learned and hurdles both cleared & still standing. In essence, this book highlights how their humanity coupled with innovative solutions to “Big Data” is changing humanitarian response forever. Digital Humanitarians will make you think differently about what it means to be humanitarian and will invite you to join the journey online. And that is what it’s ultimately all about—action, responsible & effective action.

Why did I write this book? The main reason may perhaps come as a surprise—one word: hope. In a world seemingly overrun by heart-wrenching headlines and daily reminders from the news and social media about all the ugly and cruel ways that technologies are being used to spy on entire populations, to harass, oppress, target and kill each other, I felt the pressing need to share a different narrative; a narrative about how selfless volunteers from all walks of life, from all ages, nationalities, creeds use digital technologies to help complete strangers on the other side of the planet. I’ve had the privilege of witnessing this digital good-will first hand and repeatedly over the years. This goodwill is what continues to restore my faith in humanity and what gives me hope, even when things are tough and not going well. And so, I wrote Digital Humanitarians first and fore-most to share this hope more widely. We each have agency and we can change the world for the better. I’ve seen this and witnessed the impact first hand. So if readers come away with a renewed sense of hope and agency after reading the book, I will have achieved my main objective.

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For updates on events, talks, trainings, webinars, etc, please click here. I’ll be organizing a Google Hangout on March 5th for readers who wish to discuss the book in more depth and/or follow up with any questions or ideas. If you’d like additional information on this and future Hangouts, please click on the previous link. If you wish to join ongoing conversations online, feel free to do so with the FB & Twitter hashtag #DigitalJedis. If you’d like to set up a book talk and/or co-organize a training at your organization, university, school, etc., then do get in touch. If you wish to give a talk on the book yourself, then let me know and I’d be happy to share my slides. And if you come across interesting examples of digital humanitarians in action, then please consider sharing these with other readers and myself by using the #DigitalJedis hashtag and/or by sending me an email so I can include your observation in my monthly newsletter and future blog posts. I also welcome guest blog posts on iRevolutions.

Naturally, this book would never have existed were it for digital humanitarians volunteering their time—day and night—during major disasters across the world. This book would also not have seen the light of day without the thoughtful guidance and support I received from these mentors, colleagues, friends and my family. I am thus deeply and profoundly grateful for their spirit, inspiration and friendship. Onwards!

The MicroMappers platform has come a long way and still has a ways to go. Our vision for MicroMappers is simple: combine human computing (smart crowd-sourcing) with machine computing (artificial intelligence) to filter, fuse and map a variety of different data types such as text, photo, video and satellite/aerial imagery. To do this, we have created a collection of “Clickers” for MicroMappers. Clickers are simply web-based crowdsourcing apps used to make sense of “Big Data”. The “Text Cicker” is used to filter tweets & SMS’s; “Photo Clicker” to filter photos; “Video Clicker” to filter videos and yes the Satellite & Aerial Clickers to filter both satellite and aerial imagery. These are the Data Clickers. We also have a collection of Geo Clickers that digital volunteers use to geo-tag tweets, photos and videos filtered by the Data Clickers. Note that these Geo Clickers auto-matically display the results of the crowdsourced geo-tagging on our MicroMaps like the one below.

Thanks to our Artificial Intelligence (AI) engine AIDR, the MicroMappers “Text Clicker” already combines human and machine computing. This means that tweets and text messages can be automatically filtered (classified) after some initial crowdsourced filtering. The filtered tweets are then pushed to the Geo Clickers for geo-tagging purposes. We want to do the same (semi-automation) for photos posted to social media as well as videos; although this is still a very active area of research and development in the field of computer vision.

So we are prioritizing our next hybrid human-machine computing efforts on aerial imagery instead. Just like the “Text Clicker” above, we want to semi-automate feature detection in aerial imagery by adding an AI engine to the “Aerial Clicker”. We’ve just starting to explore this with computer vision experts in Switzerland and Canada. Another development we’re eyeing vis-a-vis UAVs is live video streaming. To be sure, UAVs will increasingly be transmitting live video feeds directly to the web. This means we may eventually need to develop a “Streaming Clicker”, which would in some respects resemble our existing “Video Clicker” except that the video would be broadcasting live rather than play back from YouTube, for example. The “Streaming Clicker” is for later, however, or at least until a prospective partner organization approaches us with an immediate and compelling social innovation use-case.

In the meantime, my team & I at QCRI will continue to improve our maps (data visualizations) along with the human computing component of the Clickers. The MicroMappers smartphone apps, for example, need more work. We also need to find partners to help us develop apps for tablets like the iPad. In addition, we’re hoping to create a “Translate Clicker” with Translators Without Borders (TWB). The purpose of this Clicker would be to rapidly crowdsource the translation of tweets, text messages, etc. This could open up rather interesting possibilities for machine translation, which is certainly an exciting prospect.

Ultimately, we want to have one and only one map to display the data filtered via the Data and Geo Clickers. This map, using (Humanitarian) OpenStreetMap as a base layer, would display filtered tweets, SMS’s, photos, videos and relevant features from satellite and UAV imagery. Each data type would simply be a different layer on this fused “Meta-Data Crisis Map”; and end-users would simply turn individual layers on and off as needed. Note also the mainstream news feeds (CNN and BBC) depicted in the above image. We’re working with our partners at UN/OCHA, GDELT & SBTF to create a “3W Clicker” to complement our MicroMap. As noted in my forthcoming book, GDELT is the ultimate source of data for the world’s digitized news media. The 3Ws refers to Who, What, Where; an important spreadsheet that OCHA puts together and maintains in the aftermath of major disasters to support coordination efforts.

In response to Typhoon Ruby in the Philippines, Andrej Verity (OCHA) and I collaborated with Kalev Leetaru from GDELT to explore how the MicroMappers “3W Clicker” might work. The result is the Google Spreadsheet below (click to enlarge) that is automatically updated every 15 minutes with the latest news reports that refer to one or more humanitarian organizations in the Philippines. GDELT includes the original URL of the news article as well as the list of humanitarian organizations referenced in the article. In addition, GDELT automatically identifies the locations referred to in the articles, key words (tags) and the date of the news article. The spreadsheet below is already live and working. So all we need now is the “3W Clicker” to crowdsource the “What”.

The first version of the mock-up we’ve created for the “3W Clicker” is displayed below. Digital volunteers are presented with an interface that includes an news article with the names of humanitarian organizations highlighted in red for easy reference. GDELT auto-populates the URL, the organization name (or names if there are more than one) and the location. Note that both the “Who” & “Where” information can be edited directly by the volunteer incase GDELT’s automated algorithm gets those wrong. The main role of digital volunteers, however, would simply be to identify the “What” by quickly skimming the article.

The output of the “3W Clicker” would simply be another MicroMap layer. As per Andrej’s suggestion, the resulting data could also be automatically pushed to another Google Spreadsheet in HXL format. We’re excited about the possibilities and plan to move forward on this sooner rather than later. In addition to GDELT, pulling in feeds from CrisisNET may be worth exploring. I’m also really keen on exploring ways to link up with the Global Disaster Alert & Coordination System (GDACS) as well as GeoFeedia.

In the meantime, we’re hoping to pilot our “Satellite Clicker” thanks to recent conversations with Planet Labs and SkyBox Imaging. Overlaying user-generated content such as tweets and images on top of both satellite and aerial imagery can go a long way to helping verify (“ground truth”) social media during disasters and other events. This is evidenced by recent empirical studies such as this one in Germany and this one in the US. On this note, as my QCRI colleague Heather Leson recently pointed out, the above vision for MicroMappers is still missing one important data feed; namely sensors—the Internet of Things. She is absolutely spot on, so we’ll be sure to look for potential pilot projects that would allow us to explore this new data source within MicroMappers.

The above vision is a tad ambitious (understatement). We really can’t do this alone. To this end, please do get in touch if you’re interested in joining the team and getting MicroMappers to the next level. Note that MicroMappers is free and open source and in no way limited to disaster response applications. Indeed, we recently used the Aerial Clicker for this wildlife protection project in Namibia. This explains why our friends over at National Geographic have also expressed an interest in potentially piloting the MicroMappers platform for some of their projects. And of course, one need not use all the Clickers for a project, simply the one(s) that make sense. Another advantage of MicroMappers is that the Clickers (and maps) can be deployed very rapidly (since the platform was initially developed for rapid disaster response purposes). In any event, if you’d like to pilot the platform, then do get in touch.

Every Click you made on MicroMappers was a gift. Typhoon Ruby (Hagupit) disrupted the lives of many and caused damage in regions already affected by previous disasters. As MicroMappers, you gave your time, clicks and skills to make a difference. Catherine, the Head of the UN’s Information Management Unit in the Philippines had this to say: “I would like to thank all the volunteers […] for their invaluable contribution over the past few days. We are lucky that Hagupit [Ruby] made less damages than expected and that the emergency quickly scaled down.”

MicroMappers and our partners at the Standby Task Force (SBTF) were activated by the United Nations Office for the Coordination of Humanitarian Affairs (OCHA). The Mission?

To augment the situational awareness of humanitarian actors on the ground by making sense of social media generated following the Typhoon.

Over the course of 72 hours, these Digital Jedis united to MicroMap one Click at a time. By reviewing tweets and image, each MicroMapper built collective intelligence and insights that were used to build a comprehensive situational awareness reports and maps for the UN. Many hands, and in this case, Clicks, make light work.

As Catherine rightly notes, there was thankfully less damage than many feared. This explains why our MicroMaps (above and below) are thankfully not riddled with hundreds of markers. In addition, we prioritize quality over quantity at MicroMappers. Our UN partners had specifically asked for tweets related to:

Together, these tweets—which are mapped above—represented less than 5% of the Ruby-related tweets that were collected during the first 72 hours of the Typhoon making landfall. This doesn’t mean that only 5% of the information on Twitter was relevant for emergency response, however. Indeed, we also tagged tweets that were not related to the above 3 categories but that were still informative. These constituted more than 20% of all tweets collected (which are not included in the map above). In the analysis provided to UN partners, we did include a review of those other relevant tweets.

Some 700 Digital Jedis joined the response online, a new record for MicroMappers! An astounding 50,394 Clicks were made using the Text Clicker pictured above (each tweet was reviewed by at least 3 digital volunteers for quality assurance purposes). And a further 3,555 Clicks were carefully made by the SBTF to geo-locate (map) relevant tweets. In other words, close to 55,000 Clicks went into making the high quality map displayed above! That’s over 12 Clicks per minute non-stop for more than 4,300 consecutive minutes!

The United Nations also asked Digital Jedis to identify pictures posted on Twitter that showed disaster damage. Over 30,000 Clicks went into this operation with a further 7,413 Clicks made by the SBTF to map images that showed severe and mild damage. In sum, over 40,000 Clicks went into the MicroMap above. Overall, the entire MicroMappers response was powered by close to 100,000 Clicks!

Digital Jedis have yet again shown that together, we can help people get positively involved in their world, even when half-a-globe and many timezones away. Yes, we can and should donate $$ to support relief efforts and good causes around the world but we can also get directly involved by donating our time, or what we call M&M’s, Minutes and Mouse clicks. This year MicroMappers have mobilized to support wildlife protection in Namibia, food security efforts in the Philippines and of course this most recent response to Typhoon Ruby. On that note, thanks again to all volunteers who supported the MicroMappers response to the Typhoon in partnership with the United Nations. You truly are Digital Jedis! And the UK Guardian certainly agrees, check out their article on our digital response.

So what’s next? We will continue to solicit your feedback on how to improve the Clickers and will get started right away. (Add your MicroMappers feedback here). In the meantime, we will leave the Clickers online for newcomers who wish to practice. We are also in touch with the UN and UAV partners in the Philippines as they may soon fly their small, remote-control planes to take aerial photographs over disaster affected areas. If they do, they will send us the photographs for analysis via MicroMappers, so stay tuned.

In closing, MicroMappers was developed by QCRI in partnership SBTF/OCHA. So a million thanks to the QCRI team and SBTF for deploying MicroMappers in support of these digital humanitarian efforts. Special thanks go to Ji Lucas, Jus Mackinnon, ChaTo Castillo, Muhammad Imran, Heather Leson, Sarah Vieweg and last but certainly not least Peter Mosur.

A new empirical and peer-reviewed study provides “the first evidence that online networks are able to produce social capital. In the case of bonding social capital, online ties are more effective in forming close networks than theory predicts.” Entitled, “Tweeting Alone? An Analysis of Bridging and Bonding Social Capital in Online Networks,” the study analyzes Twitter data generated during three large events: “the Occupy movement in 2011, the IF Campaign in 2013, and the Chilean Presidential Election of the same year.”

What is the relationship between social media and social capital formation? More specifically, how do connections established via social media—in this case Twitter—lead to the formation of two specific forms of social capital, bridging and bonding capital? Does the interplay between bridging and bonding capital online differ to what we see in face-to-face world interactions?

“Bonding social capital exists in the strong ties occurring within, often homogeneous, groups—families, friendship circles, work teams, choirs, criminal gangs, and bowling clubs, for example. Bonding social capital acts as a social glue, building trust and norms within groups, but also potentially increasing intolerance and distrust of out-group members. Bridging social capital exists in the ties that link otherwise separate, often heterogeneous, groups—so for example, individuals with ties to other groups, messengers, or more generically the notion of brokers. Bridging social capital allows different groups to share and exchange information, resources, and help coordinate action across diverse interests.” The authors emphasize that “these are not either/or categories, but that in well-functioning societies the two types or dimensions develop together.”

The study uses social network analysis to measure bonding and bridging social capital. More specifically, they use two associated metrics as indicators of social capital: closure and brokerage. “Closure refers to the level of connectedness between particular groups of members within a broader network and encourages the formation of trust and collaboration. Brokerage refers to the existence of structural holes within a network that are ’bridged’ by a particular member of the network. Brokerage permits the transmission of information across the entire network. Social capital, then, is comprised of the combination of these two elements, which interact over time.”

The authors thus analyze the “observed values for closure and brokerage over time and compare them with different simulations based on theoretical network models to show how they compare to what we would expect offline. From this, [they provide an evaluation of the existence and formation of social capital in online networks.”

The results demonstrate that “online networks show evidence of social capital and these networks exhibit higher levels of closure than what would be expected based on theoretical models. However, the presence of organizations and professional brokers is key to the formation of bridging social capital. Similar to traditional (offline) conditions, bridging social capital in online networks does not exist organically and requires the purposive efforts of network members to connect across different groups. Finally, the data show interaction between closure and brokerage goes in the right direction, moving and growing together.”

These conclusions suggest that the same metrics—closure and brokerage—can be used to monitor “City Resilience” before, during and after major disasters. This is of particular interest to me since my team and I at QCRI are collaborating with the Rockefeller Foundation’s 100 Resilient Cities initiative to determine whether social media can indeed help monitor (proxy indicators of) resilience. Recent studies have shown that changes in employment, economic activity and mobility—each of which is are drivers of resilience—can be gleamed from social media.

While more research is needed, the above findings are compelling enough for us to move forward with Rockefeller on our joint project. So we’ll be launching AIRS in early 2015. AIRS, which stands for “Artificial Intelligence for Resilient Societies” is a free and open source platform specifically designed to enable Rockefeller’s partners cities to monitor proxy indicators of resilience on Twitter.

The analysis of cell phone data can already be used to predict mobility patterns after major natural disasters. Now, a new peer-reviewed scientific study suggests that travel patterns may also be predictable using tweets generated following large disasters. In “Quantifying Human Mobility Perturbation and Resilience in Hurricane Sandy,” co-authors Qi Wang and John Taylor analyze some 700,000 geo-tagged tweets posted by ~53,000 individuals as they moved around over the course of 12 days. Results of the analysis confirm that “Sandy did impact the mobility patterns of individuals in New York City,” but this “perturbation was surprisingly brief and the mobility patterns encouragingly resilient. This resilience occurred even in the large-scale absence of mobility infrastructure.”

In sum, this new study suggests that “Human mobility appears to possess an inherent resilience—even in perturbed states—such that movement deviations, in aggregate, follow predictable patterns in hurricanes. Therefore, it may be possible to use human mobility data collected in steady states to predict perturbation states during extreme events and, as a result, develop strategies to improve evacuation effectiveness & speed critical disaster response to minimize loss of life and human suffering.”

Authors Wang and Taylor are now turning their attention to “10 other storms and typhoons that they’ve collected data on.” They hope to further demonstrate that quantifying mobility patterns before and after disasters will eventually help cities “predict mobility in the face of a future disaster, and thereby protect and serve residents better.” They also want to “understand where the ‘upper limit’ of resilience lies. ‘After Haiyan,’—the deadliest-ever Philippine Typhoon that struck last November—’there was a total breakdown in mobility patterns,’ says Taylor.”

Of course, Twitter data comes with well-knownlimitations such as demographic bias, for example. This explains why said data must be interpreted carefully and why the results simply augment rather than replace the analysis of traditional data sources used for damage after needs assessments after disasters.